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Agent Skill · 研究检索

game-architect(游戏架构师)

game-architect 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

game-architect 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 12,911。

总安装 9,864周安装 411GitHub Stars 1下载 3,288核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:game-architect(游戏架构师)
来源仓库:https://github.com/yuki001/game-architect
安装命令:
openclaw skills install game-architect
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install game-architect

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

game-architect 专注于游戏系统架构设计,覆盖战斗、UI、叙事等多个模块。适用于规划大型游戏项目结构或优化现有系统间协作关系。提供模块化设计思路与跨领域整合方案,提升整体架构合理性。可直接在 OpenClaw 中调用,无需特殊配置即可辅助设计决策。推荐根据实际项目阶段选择性应用相关章节内容。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install game-architect;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

game-architect 怎么安装?

在终端执行 openclaw skills install game-architect。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

game-architect 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

game-architect 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

game-architect 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

game-architect 用的人多吗?

公开数据是累计安装 9,864 次,近一周安装 411 次,下载 3,288 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

game-architect 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
game-architect

游戏架构师 · 本页

9,8641需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
game-architect
description
READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent.

Game Architect Skill

Game architecture domain knowledge reference. Provides paradigm selection, system design references for game project architecture.

[!NOTE] This skill contains domain knowledge only, not a workflow. Pair it with a workflow skill (e.g., OpenSpec, SpecKit) or an agent's plan mode for structured design flow.

Usage Modes

With Workflow Skill (Recommended)

When used with a workflow skill (e.g., OpenSpec, SpecKit) or in the plan mode of an agent, this skill serves as a domain knowledge plugin:

  • During requirements/spec phases: Consult the Paradigm Selection Guide and System-Specific References to inform architectural decisions
  • During design/planning phases: Use the Reference Lookup Guide below to read relevant references/ documents

Standalone

A lightweight workflow-standalone.md is also available as a self-contained design pipeline if needed.

Knowledge Mode (Query)

When user requests to query knowledge for game architecture, this skill provides a reference lookup guide to relevant references/ documents based on the task.


Reference Lookup Guide

When designing game architecture, read the relevant references/ documents based on the task:

Architecture References

WhenRead
Always (high-level structure)references/macro-design.md
Always (core principles)references/principles.md
Requirement analysisreferences/requirements.md
Choosing DDD paradigmreferences/domain-driven-design.md
Choosing Data-Driven paradigmreferences/data-driven-design.md
Choosing Prototype paradigmreferences/prototype-design.md
Evolution & extensibility reviewreferences/evolution.md
Performance optimization neededreferences/performance-optimization.md
Multiplayer support neededreferences/system-multiplayer.md

For system-specific design, see the System-Specific References table below.

System-Specific References

System CategoryReference
Foundation & Core (Logs, Timers, Modules, Events, Resources, Audio, Input)references/system-foundation.md
Time & Logic Flow (Update Loops, Async, FSM, Command Queues, Controllers)references/system-time.md
Combat & Scene (Scene Graphs, Spatial Partitioning, ECS/EC, Loading)references/system-scene.md
UI & Modules (Modules Management, MVC/MVP/MVVM, UI Management, Data Binding, Reactive)references/system-ui.md
Skill System (Attribute, Skill, Buff)references/system-skill.md
Action Combat System (HitBox, Damage, Melee, Projectiles)references/system-action-combat.md
Narrative System (Dialogue, Cutscenes, Story Flow)references/system-narrative.md
Game AI System (Movement, Pathfinding, Decision Making, Tactical)references/system-game-ai.md
Multiplayer System (Client-Server, Sync Models, Distributed Server, AOI, Communication)references/system-multiplayer.md
Algorithm & Data Structures (Pathfinding, Search, Physics, Generic Solver)references/algorithm.md

Paradigm Selection Guide

ParadigmKeyPointApplicability ScopeExamplesReference
Domain-Driven Design (DDD)OOP & Entity FirstHigh Rule Complexity. <br> Rich Domain Concepts. <br> Many Distinct Entities.Core Combat Logic, Physics Interactions, Damage/Buff Rules, Complex AI Decision.references/domain-driven-design.md
Data-Driven DesignData Layer FirstHigh Content Complexity. <br> Flow Orchestration. <br> Simple Data Management.Content: Quests, Level Design.<br>Flow: Tutorial Flow, Skill Execution, Narrative.<br>Mgmt: Inventory, Shop, Mail, Leaderboard.references/data-driven-design.md
Use-Case Driven PrototypeUse-Case Implementation FirstRapid ValidationGame Jam, Core Mechanic Testing.references/prototype-design.md

Mixing Paradigms

Most projects mix paradigms:

  1. Macro Consistency: All modules follow the same Module Management Framework.
  2. Domain for Core Entities & Rules: Use DDD for systems with high rule complexity, rich domain concepts, and many distinct entities (e.g., Combat Actors, Damage Formulas, AI Decision).
  3. Data for Content, Flow & State: Use Data-Driven for expandable content (Quests, Level Design), flow orchestration (Tutorial, Skill Execution, Narrative), and simple data management (Inventory, Shop).
  4. Hybrid Paradigms:

- 4.1 Entities as Data: Domain Entities naturally hold both data (fields) and behavior (methods). Design entities to be serialization-friendly (use IDs, keep state as plain fields) so they serve both roles without a separate data layer. - 4.2 Flow + Domain: Use data-driven flow to orchestrate the sequence/pipeline, domain logic to handle rules at each step. E.g., Skill System: flow drives cast→channel→apply, domain handles damage calc and buff interactions. - 4.3 Separate Data/Domain Layers: Only when edit-time and runtime representations truly diverge. Use a Bake/Compile step to bridge them. E.g., visual node-graph editors, compiled assets.

  1. Paradigm Interchangeability: Many systems can be validly implemented with either paradigm. E.g., Actor inheritance hierarchy (Domain) ↔ ECS components + systems (Data-Driven); Buff objects with encapsulated rules (Domain) ↔ Tag + Effect data entries resolved by a generic pipeline (Data-Driven). See Selection Criteria table above for trade-off signals.
  2. Integration: Application Layer bridges different paradigms.

Selection Criteria

When both DDD and Data-Driven fit, use these signals:

SignalFavor DDDFavor Data-Driven
Entity interactionsComplex multi-entity rules (attacker × defender × buffs × environment)Mostly CRUD + display, few cross-entity rules
Behavior sourceVaries by entity type, hard to express as pure dataDriven by config tables, designer-authored content
Change frequencyRules change with game balance iterationsContent/flow changes far more often than logic
Performance profileAcceptable overhead for rich object graphsNeeds batch processing, cache-friendly layouts
NetworkingStateful objects acceptableFlat state snapshots preferred (sync, rollback)
Team workflowProgrammers own the logicDesigners need to iterate without code changes

平台分布

OpenClaw

89.22%
按下载量换算2,934

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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